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Electrodiagnosis support system for localizing neural injury in an upper limb

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dc.contributor.authorShin, Hanjun-
dc.contributor.authorKim, Ki Hoon-
dc.contributor.authorSong, Chihwan-
dc.contributor.authorLee, Injoon-
dc.contributor.authorLee, Kyubum-
dc.contributor.authorKang, Jaewoo-
dc.contributor.authorKang, Yoon Kyoo-
dc.date.accessioned2021-09-08T03:38:58Z-
dc.date.available2021-09-08T03:38:58Z-
dc.date.created2021-06-11-
dc.date.issued2010-05-
dc.identifier.issn1067-5027-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/116579-
dc.description.abstractNeedle electromyography (EMG) is used for the diagnosis of a neural injury in patients with a cervical/lumbar radiculopathy, plexopathy, peripheral neuropathy, or myopathy. Needle EMG is a particularly invasive test and thus it is important to minimize the pain during inspections. In this paper, we introduce the Electrodiagnosis Support System (ESS), which is a clinical decision support system specialized for neural injury diagnosis in the upper limb. ESS can guide users through the diagnosis process and assist them in making the optimal decision for minimizing unnecessary inspections and as an educational tool for medical trainees. ESS provides a graphical user interface that visualizes the neural structure of the upper limb, through which users input the results of needle EMG tests and retrieve diagnosis results. We validated the accuracy of the system using the diagnosis records of 133 real patients.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherOXFORD UNIV PRESS-
dc.subjectEXPERT-SYSTEM-
dc.subjectLOCALIZATION-
dc.subjectLESIONS-
dc.titleElectrodiagnosis support system for localizing neural injury in an upper limb-
dc.typeArticle-
dc.contributor.affiliatedAuthorKang, Jaewoo-
dc.contributor.affiliatedAuthorKang, Yoon Kyoo-
dc.identifier.doi10.1136/jamia.2009.001594-
dc.identifier.scopusid2-s2.0-77955289073-
dc.identifier.wosid000277580700017-
dc.identifier.bibliographicCitationJOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, v.17, no.3, pp.345 - 347-
dc.relation.isPartOfJOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION-
dc.citation.titleJOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION-
dc.citation.volume17-
dc.citation.number3-
dc.citation.startPage345-
dc.citation.endPage347-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassahci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaHealth Care Sciences & Services-
dc.relation.journalResearchAreaInformation Science & Library Science-
dc.relation.journalResearchAreaMedical Informatics-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryHealth Care Sciences & Services-
dc.relation.journalWebOfScienceCategoryInformation Science & Library Science-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.subject.keywordPlusEXPERT-SYSTEM-
dc.subject.keywordPlusLOCALIZATION-
dc.subject.keywordPlusLESIONS-
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